Year: 2024
Type: article
Abstract: The study of oceanic atmospheres has been enhanced by the use of the Underwater Sensor Networks (UWSNs), which require acoustic channels for node-to-node communication since they are appropriate for use in underwater environments. UWSNs are distinguished by the placement of sensors at various depths in the sea and differ from the terrestrial networks. This research incorporates an EA in the UWSNs to improve the transmission efficiency in the network system. In particular, the Energy-Aware Clustering Protocol for Underwater Sensor Networks (EAC-UWSN) is improved with help of evolutionary approaches. The proposed Evolutionary Density and Grid-based Clustering Algorithm (EDA-UWSN) is a two-step process of using grid and density-based to find out the dense cells and then to clusters them optimally. The algorithm uses the probabilities of cluster generation to change transmission protocols and thereby increase efficiency. The analysis of simulation results proves that the proposed EDA-based clustering algorithm provides better performance comparing to traditional UWSN and improves the communication in the underwater networks.
Author: K.M.Padmapriya
Language: English
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4402447526